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Demand Analytics

Approx. 9 hours to complete

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Description

Welcome to Demand Analytics - one of the most sought-after skills in supply chain management and marketing!

Through the real-life story and data of a leading cookware manufacturer in North America, you will learn the data analytics skills for demand planning and forecasting. Upon the completion of this course, you will be able to 1. Improve the forecasting accuracy by building and validating demand prediction models. 2. Better stimulate and influence demand by identifying the drivers (e.g., time, seasonality, price, and other environmental factors) for demand and quantifying their impact. AK is a leading cookware manufacturer in North America. Its newly launched top-line product was gaining momentum in the marketplace. However, a price adjustment at the peak season stimulated a significant demand surge which took AK completely by surprise and resulted in huge backorders. AK faced the risk of losing the market momentum due to the upset customers and the high cost associated with over-time production and expedited shipping. Accurate demand forecast is essential for increasing revenue and reducing cost. Identifying the drivers for demand and assessing their impact on demand can help companies better influence and stimulate demand. I hope you enjoy the course!

Knowledge

Use data analytics to predict demand with trend (as in new product introduction), seasonality, price elasticity and other environmental factors.
Identify the key drivers for demand and quantify their impact.
Build, validate and improve forecasting models with both continuous and categorical variables.

Outline

Welcome!
The story of AK MetalCrafters
Course overview
General principles of demand planning and forecasting
Is this course right for me?
Four Pillars of Demand Planning Excellence
General principles

Predicting Trend
The basics of statistical forecasting models
Data collection, pre-processing and visualization
Data visualization screencast
Build and interpret a linear model
Build and interpret a linear model screencast
Software selection and preparation
The visualization example
Build and interpret a linear model: example
Predicting trend

Predicting the Impact of Price and Other Environmental Factors
Model validation and improvement
Multiple regression for trend, price and other factors
Multiple regression screencast
Multiple regression example
Model validation and improvement
Multiple regression

Predicting Seasonality
Categorical variable (seasonality) modeling and formatting
Forecasting and testing
Forecasting and testing screencast
Categorical variables example
Forecasting and testing example
Modeling and formatting categorical variables

Summary of User Reviews

Learn demand analytics and improve your business decisions with this Coursera course. Students have praised the course for its practical approach and real-world examples.

Key Aspect Users Liked About This Course

Practical approach and real-world examples

Pros from User Reviews

Great course for improving business decisions
Well-structured and easy to follow
Engaging and informative lectures
Practical assignments and case studies
Excellent support from the instructor and community

Cons from User Reviews

Some technical concepts may be challenging for beginners
Limited interaction with other students
Not enough emphasis on statistical models
Some lectures are too long and detailed
Course material can become repetitive over time

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